3i

• Probability Sampling


  Involves selecting samples based on chance events, ensuring each member of the population has an equal chance of selection
• Sample


  A subset of a larger population used to draw inferences about the entire population
• Sampling Methods


  • Random Sampling
  • Stratified Random Sampling
  • Cluster (Area) Sampling
  • Systematic Sampling
• Random Sampling


  Every member of the population has a known and equal chance of being selected
• Stratified Random Sampling


  Population divided into mutually exclusive groups, and random samples are drawn from each group
• Cluster (Area) Sampling


  Population divided into groups, and a sample of the group is selected for interview
• Systematic Sampling


  Every nth case after a random selection is selected, providing simplicity and structure to the sampling process
• Sampling Design


  The technique or procedure used for selecting items as samples from the population or universe
• Sample Size


  Determined based on who will be surveyed, how many people will be surveyed, and how the sample should be chosen
• Purpose: To understand the principles and techniques of non-probability sampling for qualitative research
• Non-Probability Sampling


  Involves selecting samples based on nonrandom criteria, where not every individual has an equal chance of inclusion
• Types of Non-Probability Samples


  • Purposive Sampling
  • Snowball Sampling
  • Quota Sampling
  • Convenience Sampling
• Purposive Sampling


  Selects participants based on specific perspectives or criteria relevant to the study
• Snowball Sampling


  Participants are identified through referrals from initial participants, useful for studying stigmatized or hard-to-reach groups
• Quota Sampling


  Participants are selected to ensure representation across important categories with anticipated variation
• Convenience Sampling


  Participants are chosen based on convenience or accessibility, often used in exploratory research or by journalists for quick access to participants
• Non-probability samples are suitable for exploratory and qualitative research, where the goal is not to make statistical inferences about the entire population but to develop initial understandings or insights
• While non-probability samples offer convenience, they carry a higher risk of sampling bias and should be used cautiously for generalizing findings to larger populations
• Statistics


  Involves the collection, analysis, interpretation, and conclusion of data
• Biostatistics


  Applies statistical techniques to biomedical data for conclusions
• Measurement scale is crucial in data collection, analysis, and presentation
• Constant


  A situation or value that does not change
• Variable


  A characteristic, number, or quantity that varies or differs
• Independent Variable


  A variable whose value affects another variable
• Dependent Variable


  A variable whose value may change due to the change in another variable
• Moderator Variable


  A variable that affects the cause-and-effect relationship between two other variables
• Controlled Variable


  A variable whose effect is controlled to isolate the relationship between other variables
• Intervening Variable


  A variable that may affect the relationship between other variables but is not measured or controlled
• Nominal


  Qualitative data assessed in terms of words or attributes
• Ordinal


  Qualitative data assessed in terms of rank order
• Discrete


  Quantitative data whose values cannot be expressed as decimals
• Continuous


  Quantitative data measured in values and can be quantified in decimals
• Primary Data Collection


  Data collected directly from research participants for the study
• Secondary Data Collection


  Data collected from published research papers for secondary research studies
• Surveys


  Conducted traditionally using paper-based or online methods, with closed-ended questions predominating
• One-on-One Interviews


  Traditionally face-to-face but now often conducted via telephone or online platforms, structured and extensive in collecting information
• Data Collection Procedure


  1. Define the Aim

  2. Develop Operational Definitions

  3. Choose Data Collection Techniques

  4. Begin Data Collection
• Data collection is foundational to research, requiring careful planning and execution to ensure the validity and reliability of the findings
• Qualitative methods


  Focus on gaining insights and understanding underlying reasons and motivations
• Qualitative methods


  • Emerged due to the limitations of traditional quantitative methods in expressing human feelings and emotions